DocumentCode
1307465
Title
Fast tracking and noise-immunised RLS algorithm based on Kalman filter
Author
Byung-Eul Jun ; Dong-Jo Park
Volume
32
Issue
25
fYear
1996
fDate
12/5/1996 12:00:00 AM
Firstpage
2311
Lastpage
2312
Abstract
A new least-squares algorithm based on the Kalman filter is presented. The algorithm has a self-perturbing term added to the covariance matrix, which keeps the gain vector from going infinitely small. It not only has a fast tracking capability, but also is immunised against measurement noise. The effectiveness of the algorithm is confirmed through computer simulations
Keywords
Kalman filters; covariance matrices; filtering theory; least squares approximations; noise; signal processing; Kalman filter; covariance matrix; fast tracking RLS algorithm; fast tracking capability; gain vector; least-squares algorithm; measurement noise; noise-immunised RLS algorithm; recursive least squares; self-perturbing term;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19961574
Filename
555946
Link To Document